-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\knm4642\Dropbox\Nha Meo Heo Beo\_JMP\WORKING FOLDER\Table I_Baseline effects.log
  log type:  text
 opened on:  18 Feb 2026, 23:44:40

. 
. //PREPARE DATA
. * set globals
. global firm = "firmage firmage2"

. global ceo = "gender age age2 yrinco i.education"

. global country = "logGDP logpop GDPgr lsc gov3_pcr logustradevol logcallpat"

. global culture = "highincome_sd getahead_sd risktakinggps_sd patiencegps_sd"

. global sample = "year < 2012 & !nonUS"

. global cluster = "mainethcode"

. 
. 
. //PREPARE TABLE
. eststo clear

. use "Baseline CEO firm year sample.dta", clear

. eststo col1: /// baseline
>         reghdfe ash_f1allpat trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      20.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0618858   .0168605     3.67   0.001     .0277232    .0960484
     firmage |  -.0109686   .0019023    -5.77   0.000    -.0148231   -.0071142
    firmage2 |   .0001159   .0000492     2.35   0.024     .0000162    .0002157
      gender |  -.0118746    .033103    -0.36   0.722    -.0789476    .0551983
         age |  -.0012187   .0103035    -0.12   0.906    -.0220956    .0196582
        age2 |  -6.07e-06   .0000846    -0.07   0.943    -.0001776    .0001654
      yrinco |   .0040659   .0005505     7.39   0.000     .0029505    .0051814
             |
   education |
          2  |   .0426374   .0480788     0.89   0.381    -.0547795    .1400544
          3  |   .0592057      .0333     1.78   0.084    -.0082666     .126678
          4  |   .0837448   .0411572     2.03   0.049     .0003525    .1671372
             |
       _cons |   .8168338   .2952368     2.77   0.009     .2186271     1.41504
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local spec               "Baseline"

added macro:
               e(spec) : "Baseline"

.                 estadd local baselineFE         "X"

added macro:
         e(baselineFE) : "X"

.                 estadd local controls           "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col1, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

.         sum f1allpat if e(sample)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
    f1allpat |     29,384    18.01814    148.4439          0       6875

.         dis _b[trust_sd] * r(mean)
1.1150665

. eststo col2: /// additional SIC3 x year fixed effects
>         reghdfe ash_f1allpat trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid sic3#year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 25 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      18.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9108
                                                  Adj R-squared   =     0.8880
                                                  Within R-sq.    =     0.0019
Number of clusters (mainethcode) =         38     Root MSE        =     0.5413

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0663282   .0171649     3.86   0.000     .0315489    .1011076
     firmage |  -.0083723   .0018732    -4.47   0.000    -.0121679   -.0045768
    firmage2 |   .0000947   .0000782     1.21   0.234    -.0000639    .0002532
      gender |   .0017937   .0349954     0.05   0.959    -.0691137    .0727011
         age |  -.0001519   .0106381    -0.01   0.989    -.0217067    .0214029
        age2 |  -.0000113   .0000884    -0.13   0.899    -.0001905    .0001678
      yrinco |   .0038174    .000507     7.53   0.000     .0027902    .0048446
             |
   education |
          2  |     .02867   .0446076     0.64   0.524    -.0617137    .1190536
          3  |   .0514752   .0335749     1.53   0.134    -.0165539    .1195043
          4  |    .064982   .0337318     1.93   0.062    -.0033651    .1333291
             |
       _cons |   .7163136   .3533401     2.03   0.050     .0003786    1.432249
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
   sic3#year |      2590         231        2359     |
-----------------------------------------------------+

.                 estadd local spec               "Ind trends"

added macro:
               e(spec) : "Ind trends"

.                 estadd local baselineFE         "X"

added macro:
         e(baselineFE) : "X"

.                 estadd local controls           "X"

added macro:
           e(controls) : "X"

.                 estadd local additionalFE       "X"

added macro:
       e(additionalFE) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col2, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col3: /// forward citation-weighted
>         reghdfe ash_f1allpat_citff trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      49.74
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8362
                                                  Adj R-squared   =     0.8132
                                                  Within R-sq.    =     0.0014
Number of clusters (mainethcode) =         38     Root MSE        =     1.1065

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1all~ff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0988601   .0285309     3.47   0.001     .0410511    .1566692
     firmage |  -.0367611   .0061776    -5.95   0.000     -.049278   -.0242442
    firmage2 |   .0001588   .0000869     1.83   0.076    -.0000173    .0003349
      gender |   .0579437   .0658497     0.88   0.385    -.0754804    .1913678
         age |  -.0194194   .0214343    -0.91   0.371    -.0628495    .0240107
        age2 |    .000171   .0001816     0.94   0.352     -.000197     .000539
      yrinco |   .0054685   .0011704     4.67   0.000     .0030971      .00784
             |
   education |
          2  |   .0076752   .1496863     0.05   0.959     -.295618    .3109684
          3  |   .0272212   .1235183     0.22   0.827    -.2230506     .277493
          4  |   .0680142    .141063     0.48   0.633    -.2178065    .3538349
             |
       _cons |   2.209405   .5727756     3.86   0.000     1.048852    3.369959
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local spec               "Fwd cites"

added macro:
               e(spec) : "Fwd cites"

.                 estadd local baselineFE         "X"

added macro:
         e(baselineFE) : "X"

.                 estadd local controls           "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col3, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col4: /// (granted) patent value-weighted
>         reghdfe ash_f1uspat_xi trust_sd ${firm} ${ceo} if ${sample} & year < 2008, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     20,218
Absorbing 2 HDFE groups                           F(  10,     37) =      16.32
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8430
                                                  Adj R-squared   =     0.8137
                                                  Within R-sq.    =     0.0028
Number of clusters (mainethcode) =         38     Root MSE        =     0.9555

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1uspa~i | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |    .114769   .0413416     2.78   0.009     .0310029    .1985351
     firmage |  -.0232782   .0093139    -2.50   0.017      -.04215   -.0044064
    firmage2 |  -.0003112   .0001553    -2.00   0.052    -.0006258    3.45e-06
      gender |   .0101102   .0604205     0.17   0.868    -.1123135    .1325338
         age |  -.0261648   .0150854    -1.73   0.091    -.0567307    .0044012
        age2 |   .0002677   .0001354     1.98   0.056    -6.69e-06     .000542
      yrinco |   .0026723   .0013325     2.01   0.052    -.0000277    .0053722
             |
   education |
          2  |  -.0374073   .0648157    -0.58   0.567    -.1687362    .0939217
          3  |   .0286571   .0498789     0.57   0.569    -.0724072    .1297214
          4  |   .1053049   .0959382     1.10   0.279    -.0890845    .2996942
             |
       _cons |   1.571845   .4673365     3.36   0.002      .624931    2.518759
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3168           0        3168     |
        year |         8           1           7     |
-----------------------------------------------------+

.                 estadd local spec               "Pat value"

added macro:
               e(spec) : "Pat value"

.                 estadd local baselineFE         "X"

added macro:
         e(baselineFE) : "X"

.                 estadd local controls           "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      20218       3168

.                 eststo col4, add(nofirms r(ndistinct))
(e(nofirms) = 3168 added)

. 
. use "CEO transition event sample.dta", clear

. gen postxdeltatrust = postchange * deltatrust if trust_sd != .
(111 missing values generated)

. gen postxtrustbf = postchange * trustbf if trust_sd != .
(111 missing values generated)

. global exoeventsample = "!bothnonUS & (retire5yr | deathwi1yr)"

. 
. eststo col5: /// retirement and death events OLS
>         reghdfe ash_f1allpat trust_sd ${firm} ${ceo} ///
>         if ${exoeventsample}, a(eventid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      3,758
Absorbing 2 HDFE groups                           F(  10,     27) =       7.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9317
                                                  Adj R-squared   =     0.9233
                                                  Within R-sq.    =     0.0056
Number of clusters (mainethcode) =         28     Root MSE        =     0.5361

                           (Std. err. adjusted for 28 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0848849   .0425261     2.00   0.056    -.0023714    .1721412
     firmage |  -.0194418   .0061031    -3.19   0.004    -.0319643   -.0069192
    firmage2 |  -.0000179   .0000679    -0.26   0.794    -.0001571    .0001214
      gender |  -.1115255   .1078749    -1.03   0.310    -.3328665    .1098154
         age |   .0043571   .0115194     0.38   0.708    -.0192787     .027993
        age2 |  -.0000527   .0001092    -0.48   0.633    -.0002767    .0001713
      yrinco |   .0013758    .001349     1.02   0.317    -.0013921    .0041436
             |
   education |
          2  |   .2127493   .0827792     2.57   0.016     .0429004    .3825983
          3  |   .1683189   .0822764     2.05   0.051    -.0004984    .3371362
          4  |   .2897445   .1014536     2.86   0.008      .081579    .4979101
             |
       _cons |   1.332825   .3740119     3.56   0.001     .5654155    2.100233
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     eventid |       388           0         388     |
        year |        13           1          12     |
-----------------------------------------------------+

.                 estadd local spec               "Retd/died"

added macro:
               e(spec) : "Retd/died"

.                 estadd local baselineFE         "X"

added macro:
         e(baselineFE) : "X"

.                 estadd local controls           "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |       3758        374

.                 eststo col5, add(nofirms r(ndistinct))
(e(nofirms) = 374 added)

. eststo col6: /// retirement and death events IV
>         ivreghdfe ash_f1allpat (postxdeltatrust = postxtrustbf) postchange ${firm} ${ceo} ///
>         if ${exoeventsample}, a(eventid year) cluster(mainethcoder) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on mainethcoder

Number of clusters (mainethcoder) =     51            Number of obs =     3758
                                                      F( 11,    50) =     5.26
                                                      Prob > F      =   0.0000
Total (centered) SS     =  967.8062459                Centered R2   =   0.0057
Total (uncentered) SS   =  967.8062459                Uncentered R2 =   0.0057
Residual SS             =  962.2469273                Root MSE      =    .5362

---------------------------------------------------------------------------------
                |               Robust
   ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
postxdeltatrust |   .0824844   .0464542     1.78   0.082    -.0108216    .1757903
     postchange |  -.0647301   .0403166    -1.61   0.115    -.1457084    .0162483
        firmage |  -.0232746   .0056804    -4.10   0.000    -.0346841   -.0118651
       firmage2 |  -.0000106   .0001111    -0.10   0.925    -.0002336    .0002125
         gender |  -.1144188   .0900087    -1.27   0.210    -.2952067     .066369
            age |   .0049401   .0137552     0.36   0.721     -.022688    .0325681
           age2 |  -.0000835   .0001204    -0.69   0.491    -.0003254    .0001584
         yrinco |   .0008445   .0011285     0.75   0.458    -.0014222    .0031113
                |
      education |
             0  |          0  (empty)
             2  |   .2144293   .1041217     2.06   0.045     .0052948    .4235638
             3  |   .1742841   .1035664     1.68   0.099    -.0337352    .3823033
             4  |    .293476   .0925513     3.17   0.003     .1075812    .4793707
---------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             10.020
                                                   Chi-sq(1) P-val =    0.0015
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):             2168.055
                         (Kleibergen-Paap rk Wald F statistic):        957.428
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         postxdeltatrust
Included instruments: postchange firmage firmage2 gender age age2 yrinco
                      2.education 3.education 4.education
Excluded instruments: postxtrustbf
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     eventid |       388           0         388     |
        year |        13           1          12     |
-----------------------------------------------------+

.                 estadd local spec               "Retd/died IV"

added macro:
               e(spec) : "Retd/died IV"

.                 estadd local baselineFE         "X"

added macro:
         e(baselineFE) : "X"

.                 estadd local controls           "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |       3758        374

.                 eststo col6, add(nofirms r(ndistinct))
(e(nofirms) = 374 added)

. 
. use "Baseline CEO firm year sample.dta", clear

. eststo col7: /// country of origin controls
>         reghdfe ash_f1allpat trust_sd ${firm} ${ceo} ${country} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  17,     37) =      32.17
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0027
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                            (Std. err. adjusted for 38 clusters in mainethcode)
-------------------------------------------------------------------------------
              |               Robust
 ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
     trust_sd |   .0420488   .0172957     2.43   0.020     .0070044    .0770933
      firmage |  -.0113681    .001957    -5.81   0.000    -.0153333   -.0074029
     firmage2 |    .000118   .0000486     2.43   0.020     .0000196    .0002165
       gender |  -.0148526    .033424    -0.44   0.659    -.0825759    .0528708
          age |   -.001035   .0104049    -0.10   0.921    -.0221172    .0200473
         age2 |  -6.59e-06   .0000858    -0.08   0.939    -.0001805    .0001673
       yrinco |   .0040702   .0005288     7.70   0.000     .0029988    .0051416
              |
    education |
           2  |   .0449075    .046238     0.97   0.338    -.0487796    .1385947
           3  |    .060554   .0322567     1.88   0.068    -.0048043    .1259123
           4  |   .0869376    .039394     2.21   0.034     .0071179    .1667574
              |
       logGDP |   -.009598   .0260622    -0.37   0.715     -.062405     .043209
       logpop |  -.0023069   .0200257    -0.12   0.909    -.0428828     .038269
        GDPgr |   .0042537   .0022947     1.85   0.072    -.0003958    .0089032
          lsc |  -.0003502   .0006731    -0.52   0.606     -.001714    .0010136
     gov3_pcr |     .04685   .1053456     0.44   0.659    -.1666005    .2603005
logustradevol |   .0171859   .0104563     1.64   0.109    -.0040007    .0383725
   logcallpat |  -.0059161   .0134994    -0.44   0.664    -.0332686    .0214363
        _cons |    1.04829   .4650387     2.25   0.030     .1060321    1.990548
-------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local spec               "Country ctrls"

added macro:
               e(spec) : "Country ctrls"

.                 estadd local baselineFE         "X"

added macro:
         e(baselineFE) : "X"

.                 estadd local controls           "X"

added macro:
           e(controls) : "X"

.                 estadd local countrycontrols    "X"

added macro:
    e(countrycontrols) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col7, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col8: /// other cultural trait controls
>         reghdfe ash_f1allpat trust_sd ${firm} ${ceo} ${culture} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  14,     37) =      14.16
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0026
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                               (Std. err. adjusted for 38 clusters in mainethcode)
----------------------------------------------------------------------------------
                 |               Robust
    ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
        trust_sd |   .0535951   .0230369     2.33   0.026      .006918    .1002723
         firmage |  -.0114257   .0021058    -5.43   0.000    -.0156924    -.007159
        firmage2 |   .0001162   .0000493     2.36   0.024     .0000163    .0002161
          gender |  -.0153099   .0330532    -0.46   0.646     -.082282    .0516622
             age |  -.0015353   .0105177    -0.15   0.885    -.0228462    .0197757
            age2 |  -3.11e-06   .0000864    -0.04   0.972    -.0001783     .000172
          yrinco |   .0040697     .00057     7.14   0.000     .0029148    .0052246
                 |
       education |
              2  |    .044679   .0472237     0.95   0.350    -.0510053    .1403632
              3  |   .0598988    .033015     1.81   0.078     -.006996    .1267936
              4  |   .0833378   .0412954     2.02   0.051    -.0003347    .1670102
                 |
   highincome_sd |    .056645   .0265628     2.13   0.040     .0028237    .1104663
     getahead_sd |   .0324636    .019856     1.63   0.111    -.0077684    .0726956
risktakinggps_sd |    .009276   .0177359     0.52   0.604    -.0266603    .0452123
  patiencegps_sd |   .0039886   .0227563     0.18   0.862      -.04212    .0500971
           _cons |   .2593156   .3260705     0.80   0.432     -.401366    .9199973
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local spec               "Other traits"

added macro:
               e(spec) : "Other traits"

.                 estadd local baselineFE         "X"

added macro:
         e(baselineFE) : "X"

.                 estadd local controls           "X"

added macro:
           e(controls) : "X"

.                 estadd local culturalcontrols   "X"

added macro:
   e(culturalcontrols) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col8, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. 
. esttab /*using "Table I_Baseline effects.tex"*/, ///
>         cells(b(star fmt(3)) se(par fmt(3))) starlevels(* 0.1 ** 0.05 *** 0.01) ///
>         nomtitle collabels(none) label varwidth(29) modelwidth(12) ///
>         mgroups("arsinh(Future patent applications)", pattern(1 0 0 0 0 0 0 0) ///
>                 prefix(\multicolumn{@span}{c}{) suffix(}) span) ///
>         keep(trust_sd postxdeltatrust) order(trust_sd postxdeltatrust) ///
>         coeflab(trust_sd "CEO's trust" postxdeltatrust "Post $\times$ Change in trust") ///
>         stats(spec baselineFE controls additionalFE countrycontrols culturalcontrols N nofirms, ///
>                 fmt(%9.0fc %9.0fc) ///
>                 lab("Specification" "Firm \& Year FEs" "Baseline controls" "Industry $\times$ Year FEs" ///
>                         "Home country controls" "Other cultural traits" "Observations" "Firms"))

-------------------------------------------------------------------------------------------------------------------------------------------------------------
                              \multicolumn{8}{c}{arsinh(Future patent applications)}                                                                         
                                       (1)             (2)             (3)             (4)             (5)             (6)             (7)             (8)   
-------------------------------------------------------------------------------------------------------------------------------------------------------------
CEO's trust                          0.062***        0.066***        0.099***        0.115***        0.085*                          0.042**         0.054** 
                                   (0.017)         (0.017)         (0.029)         (0.041)         (0.043)                         (0.017)         (0.023)   
Post $\times$ Change in trust                                                                                        0.082*                                  
                                                                                                                   (0.046)                                   
-------------------------------------------------------------------------------------------------------------------------------------------------------------
Specification                     Baseline      Ind trends       Fwd cites       Pat value       Retd/died    Retd/died IV    Country ctrls    Other traits   
Firm \& Year FEs                         X               X               X               X               X               X               X               X   
Baseline controls                        X               X               X               X               X               X               X               X   
Industry $\times$ Year FEs                               X                                                                                                   
Home country controls                                                                                                                    X                   
Other cultural traits                                                                                                                                    X   
Observations                        29,384          29,384          29,384          20,218           3,758           3,758          29,384          29,384   
Firms                                3,598           3,598           3,598           3,168             374             374           3,598           3,598   
-------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. cap log close
